To store time-domain distribution data of spatially discrete physical quantities (physical quantity distribution data), a storage region determined by space (discrete distribution points)×time is used. For example, in the case of FDTD method for solving Maxwell's equation with a difference method in time and space in three dimensional electromagnetic wave analysis, a calculation result thereof is stored in a storage region of 100×100×100×1e−9/10e−15 steps×4 bytes×2=800 GB where computational grid is 100×100×100, a time step is 10 fs, an analysis time is 1 ns, and electric field and magnetic field calculation results of a single cell are stored in a single precision (float type) of 4 bytes.
Since distribution data is stored by using huge resources in a conventional technique, the storage region is reduced by decimating the distribution data by time and space (spatial data for interpolation is calculated from the calculation result which is performed based on the decimated distribution data by setting the storage interval of the distribution data to every n times when the distribution data is to be stored) or by applying a general compression algorithm to the distribution data.
Another conventional technique is also known in which a plurality of structure parameter values used in numeric analysis are read as variable dependent information, conversion information is generated from the variable dependent information, the result information of the numeric analysis is converted on the basis of the conversion information, and the converted result information of the numeric analysis is compressed (see, for example, Japanese Laid-open Patent Publication No. 2007-249338).
If distribution data of an object having a fine or a complex shape in a space is decimated by space and time, the precision and resolution of the distribution data degrade. Thus, the conventional technique is not expected to produce a large effect of reducing the storage region in a practical space model. In addition, the conventional technique has problems of taking recalculation time for displaying the distribution data on physical quantities in a space, and of using a large storage region for displaying the entire region in the space in detail.
Furthermore, the physical quantity distribution data has a small redundancy of physical quantity between spatially adjacent distribution points and depends on a calculation model condition. Therefore, the physical quantity distribution data has such a spatially complex distribution that the application of the general compression algorithm is not expected to yield a high compression ratio.